Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

In cyber security, the most crucial subject in information security is user authentication. Robust text-based password methods may offer a certain level of protection. Strong passwords are hard to remember, though, so people who use them frequently write them on paper or store them in file for computer .Numerous of computer systems, networks, and Internet-based environments have experimented with using graphical authentication techniques for user authentication in recent years. The two main characteristics of all graphical passwords are their security and usability. Regretfully, none of these methods could adequately address both of these factors concurrently. The ISO usability standards and associated characteristics for graphical

For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

Experimentation Multi effective and fertile grew human desire to discover new ways to express beauty in artwork .And dabble term experimentation in the performing arts and arts architecture, cinema and television in the test forms and interest in the visual effects and movements seek to establish and beauty and schools of thought in literature and art. This study aims to identify

Thin films of iridium doped indium oxide (In2O3:Eu)with different doping ratio(0,3,5,7,and 9%) are prepared on glass and single crystal silicon wafer substrates using spray pyrolysis method. The goal of this research is to investigate the effect of doping ratio on of the structural, optical and sensing properties . The structure of the prepared thin films was characterized at room temperature using X-ray diffraction. The results showed that all the undoped and doped (In2O3:Eu)samples are polycrystalline in structure and nearly stoichiometric. UV-visible spectrophotometer in the wavelength range (200-1100nm)was used to determine the optical energy gap and optical constants. The optical transmittance of 83% and the optical band gap of 5.2eV

In this study, SnS thin films were deposited onto glass substrate by thermal evaporation technique at 300K temperature. The SnS films have been prepared with different thicknesses (100,200 &300) nm. The crystallographic analysis, film thickness, electrical conductivity, carrier concentration, and carrier mobility were characterized. Measurements showed that depending on film thickness. The D.C. conductivity increased with increase in film thickness from 3.720x10-5 (Ω.cm)-1 for 100 nm thickness to 9.442x10-4 (Ω.cm)-1 for 300 nm thicknesses, and the behavior of activation energies, hall mobility, and carrier concentration were also studied.

The research consisted of four chapters, the first of which wasa methodological framework. The problem of research was determined by a question drawn up by the researcher as follows: What are the intellectual contents of science fiction films ?. The main objective of the research was to uncover the intellectual contents of contemporary science fiction films. The most important research terms (content, thought, ideology, science fiction, contemporary) were defined as either the second chapter (the theoretical framework) The second topic was entitled "The Intellectual Contents of Contemporary Science Fiction Films", in which the films of the science fiction and its current intellectual contents were discussed. The third topic included the

Optical detector was manufactured Bashaddam thermal evaporation technique at room temperature under pressure rays studied characteristics of reactive Scout efficiency quantitative ratio of the signal and the ability equivalent to noise